Can it help with intermittent or flaky test failures?

Yes, it includes protocols for documenting reproduction steps and gathering diagnostic data at component boundaries to isolate non-deterministic issues.

What is the core principle of this debugging skill?

The core principle is that if you cannot explain exactly why a bug is happening, you are not ready to fix it. Every solution must address a verified root cause.

Does it support specific programming languages?

The systematic approach is language-agnostic and applies to all technical domains, including frontend, backend, mobile, and infrastructure as code.

How does this skill improve the debugging process?

It enforces a structured methodology that requires understanding the specific reason for a failure before writing any code, which prevents time-wasting trial-and-error attempts.

Systematic Debugging

Name: Systematic Debugging
Author: Light-Brands

byLight-Brands

보안 및 테스팅

Implements a rigorous, evidence-based methodology for identifying root causes and resolving complex software bugs without guesswork.

소개

The Systematic Debugging skill provides a structured framework for diagnosing technical issues, ranging from simple test failures to deep architectural regressions. It guides Claude to prioritize evidence gathering through stack trace analysis and data flow tracing before attempting any code changes. By enforcing a 'root cause first' philosophy, the skill ensures that fixes are targeted and verified, preventing the common pitfall of layering patches on top of misunderstood problems. It is particularly effective for resolving persistent bugs, performance bottlenecks, and unexpected system behaviors in complex environments.

주요 기능

Backward data flow tracing to isolate the source of erroneous values
Evidence-based root cause analysis using logs and stack traces
0 GitHub stars
Systematic comparison between working and broken code implementations
Hypothesis-driven testing to verify causes with minimal changes
Architectural pattern recognition to identify fundamental system flaws

사용 사례

Investigating non-deterministic bugs or unexpected system behavior
Diagnosing performance regressions in multi-component architectures
Troubleshooting persistent test failures or CI/CD build errors

소개

주요 기능

Backward data flow tracing to isolate the source of erroneous values
Evidence-based root cause analysis using logs and stack traces
0 GitHub stars
Systematic comparison between working and broken code implementations
Hypothesis-driven testing to verify causes with minimal changes
Architectural pattern recognition to identify fundamental system flaws

사용 사례

Investigating non-deterministic bugs or unexpected system behavior
Diagnosing performance regressions in multi-component architectures
Troubleshooting persistent test failures or CI/CD build errors